Analyzing National Zakat Trends: Holt–Winters–Based Forecasting to Support BAZNAS Strategic Planning
DOI:
https://doi.org/10.29040/jiei.v11i06.18611Keywords:
Keywords: exponential smoothing, forecasting, multiplicative Holt–Winters, seasonalAbstract
Abstract
The National Amil Zakat Agency (BAZNAS) is a non-structural government institution mandated to collect, manage, and distribute zakat at the national level in a professional and accountable manner. As the state authority for zakat, BAZNAS plays a strategic role in ensuring the sustainability of welfare programs, making the ability to accurately forecast zakat revenue essential for planning and decision-making. This study analyzes historical patterns and forecasts the zakat revenue of BAZNAS Central for the period 2017–2025 using the multiplicative Holt–Winters method. The data indicate a consistent upward trend and strong seasonal patterns, particularly during religious periods such as Ramadan. The analysis involves identifying level, trend, and seasonal components, followed by estimating smoothing parameters and the damping factor. Two models, additive and multiplicative, were compared using AIC, AICc, and BIC, and the results show that the multiplicative model performs best. Accuracy evaluation using MSE, RMSE, and MAPE confirms that this model produces predictions that closely match the actual values. The 12-month forecast displays consistent seasonal fluctuations, with the peak of zakat collection predicted to occur in March 2026. These findings highlight the importance of incorporating seasonal time-series approaches to support strategic planning and enhance the effectiveness of national zakat management.
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